#include <opencv2/opencv.hpp>
#include <opencv2/imgproc.hpp>

#include "MotionDetection.hpp"

#if CV_MAJOR_VERSION >= 2 && CV_MAJOR_VERSION <= 3

#include "graph.h"
#include "MEHistogram.hpp"
#include "MEImage.hpp"

namespace bgslibrary
{
  namespace algorithms
  {
    namespace lbp_mrf
    {
      // Pyramid picture for the tracking
      IplImage *HUOFPyramid;
      // Pyramid picture for the tracking
      IplImage *HUOFPrevPyramid;

      // Struct for histogram update data of a pixel
      struct MEPixelDataType
      {
        float BackgroundRate;
        int LifeCycle;
        float *Weights;
        bool *BackgroundHistogram;
        float **Histograms;
        float *PreviousHistogram;
      };

      MotionDetection::MotionDetection(DetectorType mode) :
        MDMode(md_NotDefined), MDDataState(ps_Uninitialized), Frames(0), ReadyMask(false),
        HUColorSpace(MEImage::csc_RGBtoCIELuv), HULBPMode(MEImage::lbp_Special),
        HUHistogramsPerPixel(3), HUHistogramArea(5), HUHistogramBins(8),
        HUImageWidth(-1), HUImageHeight(-1), HULBPPixelData(NULL),
        HUPrThres(0.75), HUBackgrThres(0.95), HUHistLRate(0.01), HUWeightsLRate(0.01),
        HUSamplePixels(-1), HUDesiredSamplePixels(-1), HUMinCutWeight(8.0),
        HUOFDataState(ps_Uninitialized), HUOFPointsNumber(-1),
        HUOFCamMovementX(0), MaxTrackedPoints(0), HUOFFrames(-1),
        HUOFCamMovement(false)
      {
        HUOFPyramid = NULL;
        HUOFPrevPyramid = NULL;
        HUOFPoints[0] = NULL;
        HUOFPoints[1] = NULL;
        SetMode(mode);
      }

      MotionDetection::~MotionDetection()
      {
        if (MDMode != md_NotDefined)
        {
          ReleaseData();
        }
      }

      void MotionDetection::SetMode(DetectorType newmode)
      {
        if (MDMode != md_NotDefined && MDMode != newmode)
        {
          ReleaseData();
          Frames = 0;
          HUOFFrames = -1;
          HUOFCamMovement = false;
          HUOFCamMovementX = 0;
          ReadyMask = false;
        }

        switch (newmode)
        {
        case md_LBPHistograms:
          MDMode = md_LBPHistograms;
          break;

        case md_DLBPHistograms:
          MDMode = md_DLBPHistograms;
          break;

        default:
          MDMode = md_LBPHistograms;
          break;
        }
      }

      float MotionDetection::GetParameter(ParametersType param) const
      {
        float ret = 0.0;

        switch (param)
        {
        case mdp_HUProximityThreshold:
          ret = (float)HUPrThres;
          break;

        case mdp_HUBackgroundThreshold:
          ret = (float)HUBackgrThres;
          break;

        case mdp_HUHistogramLearningRate:
          ret = (float)HUHistLRate;
          break;

        case mdp_HUWeightsLearningRate:
          ret = (float)HUWeightsLRate;
          break;

        case mdp_HUMinCutWeight:
          ret = (float)HUMinCutWeight;
          break;

        case mdp_HUDesiredSamplePixels:
          ret = (float)HUDesiredSamplePixels;
          break;

        case mdp_HUHistogramsPerPixel:
          ret = (float)HUHistogramsPerPixel;
          break;

        case mdp_HUHistogramArea:
          ret = (float)HUHistogramArea;
          break;

        case mdp_HUHistogramBins:
          ret = (float)HUHistogramBins;
          break;

        case mdp_HUColorSpace:
          ret = (float)HUColorSpace;
          break;

        case mdp_HULBPMode:
          ret = (float)HULBPMode;
          break;

        default:
          break;
        }
        return ret;
      }

      void MotionDetection::SetParameter(ParametersType param, float value)
      {
        switch (param)
        {
        case mdp_HUProximityThreshold:
          HUPrThres = (float)value;
          break;

        case mdp_HUBackgroundThreshold:
          HUBackgrThres = (float)value;
          break;

        case mdp_HUHistogramLearningRate:
          HUHistLRate = (float)value;
          break;

        case mdp_HUWeightsLearningRate:
          HUWeightsLRate = (float)value;
          break;

        case mdp_HUMinCutWeight:
          HUMinCutWeight = (float)value;
          break;

        case mdp_HUDesiredSamplePixels:
          HUDesiredSamplePixels = (int)value;
          break;

        case mdp_HUHistogramsPerPixel:
          HUHistogramsPerPixel = (MDDataState == ps_Uninitialized) ? (int)value : HUHistogramsPerPixel;
          break;

        case mdp_HUHistogramArea:
          HUHistogramArea = (MDDataState == ps_Uninitialized) ? (int)value : HUHistogramArea;
          break;

        case mdp_HUHistogramBins:
          HUHistogramBins = (MDDataState == ps_Uninitialized) ? (int)value : HUHistogramBins;
          break;

        case mdp_HUColorSpace:
          HUColorSpace = (MDDataState == ps_Uninitialized) ? (int)value : HUColorSpace;
          break;

        case mdp_HULBPMode:
          HULBPMode = (MDDataState == ps_Uninitialized) ? (int)value : HULBPMode;
          break;

        default:
          break;
        }
      }

      void MotionDetection::DetectMotions(MEImage& image)
      {
        switch (MDMode)
        {
        case md_LBPHistograms:
        case md_DLBPHistograms:
          DetectMotionsHU(image);
          break;

        default:
          break;
        }
      }

      void MotionDetection::GetMotionsMask(MEImage& mask_image)
      {
        if (ReadyMask)
        {
          mask_image = MaskImage;
        }

        switch (MDMode)
        {
        case md_LBPHistograms:
        case md_DLBPHistograms:
          GetMotionsMaskHU(MaskImage);
          break;

        default:
          break;
        }

        ReadyMask = true;
        mask_image = MaskImage;
      }

      void MotionDetection::CalculateResults(MEImage& referenceimage, int& tnegatives, int& tpositives,
        int& ttnegatives, int& ttpositives)
      {
        if (MDDataState != ps_Successful)
        {
          printf("No data for calculation.\n");
          return;
        }

        if (referenceimage.GetLayers() != 1)
          referenceimage.ConvertToGrayscale(MEImage::g_OpenCV);

        referenceimage.Binarize(1);

        MEImage mask_image;

        GetMotionsMask(mask_image);

        if ((mask_image.GetWidth() != referenceimage.GetWidth()) ||
          (mask_image.GetHeight() != referenceimage.GetHeight()))
        {
          printf("Different resolutions of mask<->reference image.\n");
          return;
        }

        unsigned char* RefMaskImgData = referenceimage.GetImageData();
        unsigned char* MaskImgData = mask_image.GetImageData();
        int RowStart = 0;
        int RowWidth = referenceimage.GetRowWidth();

        int TrueNegatives = 0;
        int TruePositives = 0;
        int TotalTrueNegatives = 0;
        int TotalTruePositives = 0;

        int ImageFrame = 0;

        if (MDMode == md_LBPHistograms || md_DLBPHistograms)
        {
          ImageFrame = HUHistogramArea / 2;
        }

        for (int y = referenceimage.GetHeight() - ImageFrame - 1; y >= ImageFrame; --y)
        {
          for (int x = referenceimage.GetWidth() - ImageFrame - 1; x >= ImageFrame; --x)
          {
            TrueNegatives +=
              (RefMaskImgData[RowStart + x] == 0) &&
              (MaskImgData[RowStart + x] == 0);
            TotalTrueNegatives += (RefMaskImgData[RowStart + x] == 0);
            TruePositives +=
              (RefMaskImgData[RowStart + x] == 255) &&
              (MaskImgData[RowStart + x] == 255);
            TotalTruePositives += (RefMaskImgData[RowStart + x] == 255);
          }
          RowStart += RowWidth;
        }

        tnegatives = TrueNegatives;
        ttnegatives = TotalTrueNegatives;
        tpositives = TruePositives;
        ttpositives = TotalTruePositives;
      }

      void MotionDetection::ReleaseData()
      {
        if (MDMode == md_LBPHistograms || MDMode == md_DLBPHistograms)
        {
          ReleaseHUData();
        }
      }

      void MotionDetection::InitHUData(int imagewidth, int imageheight)
      {
        if ((HUImageWidth != imagewidth - HUHistogramArea + 1) ||
          (HUImageHeight != imageheight - HUHistogramArea + 1) ||
          (MDDataState == ps_Uninitialized))
        {
          if (MDDataState != ps_Uninitialized)
          {
            ReleaseHUData();
          }

          MDDataState = ps_Initialized;

          HUImageWidth = imagewidth - HUHistogramArea + 1;
          HUImageHeight = imageheight - HUHistogramArea + 1;

          HULBPPixelData = new MEPixelDataType**[HUImageWidth / 2];

          for (int i = 0; i < HUImageWidth / 2; ++i)
          {
            HULBPPixelData[i] = new MEPixelDataType*[HUImageHeight];
          }

          for (int i = 0; i < HUImageWidth / 2; ++i)
            for (int i1 = 0; i1 < HUImageHeight; ++i1)
            {
              HULBPPixelData[i][i1] = new MEPixelDataType;
              HULBPPixelData[i][i1]->Weights = new float[HUHistogramsPerPixel];
              HULBPPixelData[i][i1]->BackgroundHistogram = new bool[HUHistogramsPerPixel];
              HULBPPixelData[i][i1]->Histograms = new float*[HUHistogramsPerPixel];
              for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                HULBPPixelData[i][i1]->Histograms[i2] = new float[HUHistogramBins];
              HULBPPixelData[i][i1]->PreviousHistogram = new float[HUHistogramBins];
            }

          // Allocate auxiliary variables
          HUMaskColumnAddDel = new int*[HUHistogramArea];
          for (int i = 0; i < HUHistogramArea; ++i)
            HUMaskColumnAddDel[i] = new int[2];

          HUMaskRowAddDel = new int*[HUHistogramArea];
          for (int i = 0; i < HUHistogramArea; ++i)
            HUMaskRowAddDel[i] = new int[2];

          // Generate sample mask
          SetSampleMaskHU(sm_Circle, HUDesiredSamplePixels);

          // Init HU optical flow data
          if (MDMode == md_DLBPHistograms)
            InitHUOFData(imagewidth, imageheight);

          ClearHUData();
        }
      }

      void MotionDetection::InitHUOFData(int imagewidth, int imageheight)
      {
        if (HUOFDataState != ps_Uninitialized)
        {
          ReleaseHUOFData();
        }

        if (HUOFDataState == ps_Uninitialized)
        {
          HUOFPointsNumber = imagewidth*imageheight / 1000;
          HUOFPyramid = cvCreateImage(cvSize(imagewidth, imageheight), 8, 1);
          HUOFPrevPyramid = cvCreateImage(cvSize(imagewidth, imageheight), 8, 1);
          HUOFPoints[0] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber * sizeof(HUOFPoints[0][0]));
          HUOFPoints[1] = (CvPoint2D32f*)cvAlloc(HUOFPointsNumber * sizeof(HUOFPoints[1][0]));
        }
      }

      void MotionDetection::ReleaseHUData()
      {
        if (MDDataState != ps_Uninitialized)
        {
          for (int i = 0; i < HUImageWidth / 2; i++)
            for (int i1 = 0; i1 < HUImageHeight; i1++)
            {
              delete[] HULBPPixelData[i][i1]->PreviousHistogram;
              for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                delete[] HULBPPixelData[i][i1]->Histograms[i2];
              delete[] HULBPPixelData[i][i1]->Histograms;
              delete[] HULBPPixelData[i][i1]->BackgroundHistogram;
              delete[] HULBPPixelData[i][i1]->Weights;
              delete HULBPPixelData[i][i1];
            }

          for (int i = 0; i < HUImageWidth / 2; i++)
          {
            delete[] HULBPPixelData[i];
          }
          delete[] HULBPPixelData;

          if (MDMode == md_DLBPHistograms)
            ReleaseHUOFData();

          HUImageWidth = -1;
          HUImageHeight = -1;
          HULBPPixelData = NULL;
          MDDataState = ps_Uninitialized;

          // Release auxiliary variables
          for (int i = 0; i < HUHistogramArea; ++i)
            delete[] HUMaskColumnAddDel[i];
          delete[] HUMaskColumnAddDel;

          for (int i = 0; i < HUHistogramArea; ++i)
            delete[] HUMaskRowAddDel[i];
          delete[] HUMaskRowAddDel;

          HUMaskColumnAddDel = NULL;
          HUMaskRowAddDel = NULL;
        }
      }

      void MotionDetection::ReleaseHUOFData()
      {
        if (MDDataState != ps_Uninitialized)
        {
          if (HUOFPyramid)
          {
            cvReleaseImage(&HUOFPyramid);
            HUOFPyramid = NULL;
          }
          if (HUOFPrevPyramid)
          {
            cvReleaseImage(&HUOFPrevPyramid);
            HUOFPrevPyramid = NULL;
          }
          if (HUOFPoints[0])
          {
            cvFree(&HUOFPoints[0]);
            HUOFPoints[0] = NULL;
          }
          if (HUOFPoints[1])
          {
            cvFree(&HUOFPoints[1]);
            HUOFPoints[1] = NULL;
          }
          HUOFDataState = ps_Uninitialized;
        }
      }

      void MotionDetection::ClearHUData()
      {
        if (MDDataState != ps_Uninitialized)
        {
          for (int i = (HUImageWidth / 2) - 1; i >= 0; --i)
            for (int i1 = HUImageHeight - 1; i1 >= 0; --i1)
            {
              for (int i2 = HUHistogramsPerPixel - 1; i2 >= 0; --i2)
              {
                memset(HULBPPixelData[i][i1]->Histograms[i2], 0,
                  HUHistogramBins * sizeof(float));
                HULBPPixelData[i][i1]->Weights[i2] = 1.0 / HUHistogramsPerPixel;
                HULBPPixelData[i][i1]->BackgroundHistogram[i2] = true;
              }
              HULBPPixelData[i][i1]->BackgroundRate = 1.0;
              HULBPPixelData[i][i1]->LifeCycle = 0;
            }
          MDDataState = ps_Initialized;
        }
      }

      void MotionDetection::DetectMotionsHU(MEImage& image)
      {
        unsigned char *ImgData = NULL;
        MEImage newimage = image;
        float DiffAreas = 0;

        // Init the histogram update data structures if needs be
        if ((MDDataState == ps_Uninitialized) ||
          (HUImageWidth != newimage.GetWidth() - HUHistogramArea + 1) ||
          (HUImageHeight != newimage.GetHeight() - HUHistogramArea + 1))
        {
          InitHUData(newimage.GetWidth(), newimage.GetHeight());
        }

        if (newimage.GetLayers() == 1)
        {
          newimage.ConvertGrayscaleToRGB();
        }

        MEImage blueimage = newimage;
        blueimage.ColorSpace(MEImage::csc_RGBtoCIELuv);

        if (HUColorSpace != -1)
        {
          newimage.ColorSpace((MEImage::ColorSpaceConvertType)HUColorSpace);
        }

        if (Frames == 0)
        {
          MEImage BlueLayer;
          blueimage.GetLayer(BlueLayer, 1);
          BlueLayer.Resize(32, 24);
          PreviousBlueLayer = BlueLayer;
        }

        Frames++;

        // Detect the fast, big changes in the scene
        MEImage BlueLayer;
        blueimage.GetLayer(BlueLayer, 1);
        BlueLayer.Resize(32, 24);
        DiffAreas = BlueLayer.DifferenceAreas(PreviousBlueLayer, 12);

        if (DiffAreas > 80)
        {
          MDDataState = ps_Initialized;
          if (MDMode == md_DLBPHistograms)
            HUOFDataState = ps_Initialized;
          printf("Frame: %d - big changes in the scene (%f)", Frames, DiffAreas);
          Frames = 1;
          HUOFFrames = -1;
        }
        PreviousBlueLayer = BlueLayer;

        if (Frames == 1)
        {
          CurrentImage = image;
          PreviousImage = CurrentImage;
        }
        else
          if (Frames > 1)
          {
            PreviousImage = CurrentImage;
            CurrentImage = image;
            // Optical flow correction of the camera movements
            if (MDMode == md_DLBPHistograms)
            {
              OpticalFlowCorrection();
            }
          }

        newimage.ConvertToGrayscale(MEImage::g_OpenCV);

        if (HULBPMode != -1)
        {
          newimage.LBP((MEImage::LBPType)HULBPMode);
        }

        // Set some auxiliary variables
        ImgData = newimage.GetImageData();
        int DivisionOperator = (int)(log((double)256 / HUHistogramBins) / log((double) 2.)) + 1;

        // Downscale the image
        for (int i = newimage.GetRowWidth()*newimage.GetHeight() - 1; i >= 0; --i)
        {
          ImgData[i] >>= DivisionOperator;
        }

        UpdateModelHU(newimage, HULBPPixelData);

        // Change the state of the HU data structures
        if (MDDataState == ps_Initialized)
        {
          MDDataState = ps_Successful;
        }
        HUOFCamMovement = false;
        ReadyMask = false;
      }

      void MotionDetection::UpdateModelHU(MEImage& image, MEPixelDataType*** model)
      {
        float *CurrentHistogram = new float[HUHistogramBins];
        float *CurrentHistogram2 = new float[HUHistogramBins];
        unsigned char *ImgData = image.GetImageData();
        int RowWidth = image.GetRowWidth();
        int RowStart = (HUImageHeight - 1)*RowWidth;

        memset(CurrentHistogram, 0, HUHistogramBins * sizeof(float));
        // Calculate the first histogram
        for (int y = HUHistogramArea - 1; y >= 0; --y)
        {
          for (int x = HUHistogramArea - 1; x >= 0; --x)
          {
            if ((HUMaskRowAddDel[y][1] > x) && (HUMaskRowAddDel[y][0] <= x) &&
              (HUMaskColumnAddDel[x][1] > y) && (HUMaskColumnAddDel[x][0] <= y))
            {
              CurrentHistogram[ImgData[RowStart + HUImageWidth - 1 + x]]++;
            }
          }
          RowStart += RowWidth;
        }

        // This cycle generates the last row of histograms
        for (int y = HUImageHeight - 1; y >= 0; --y)
        {
          if (HUImageHeight - 1 > y)
          {
            // Delete and add a pixel column from the histogram data
            for (int i = HUHistogramArea - 1; i >= 0; --i)
            {
              if (HUMaskColumnAddDel[i][0] != -1)
                CurrentHistogram[ImgData[RowWidth*(y + HUMaskColumnAddDel[i][0]) + HUImageWidth - 1 + i]]++;
              if (HUMaskColumnAddDel[i][1] != -1)
                CurrentHistogram[ImgData[RowWidth*(y + HUMaskColumnAddDel[i][1]) + HUImageWidth - 1 + i]]--;
            }
          }

          if (y % 2 == HUImageWidth % 2)
          {
            MEPixelDataType* PixelData = model[(HUImageWidth - 1) / 2][y];

            // Allocate and initialize the pixel data if needs be
            if (!PixelData)
            {
              // Memory allocation
              PixelData = new MEPixelDataType;
              PixelData->Weights = new float[HUHistogramsPerPixel];
              PixelData->BackgroundHistogram = new bool[HUHistogramsPerPixel];
              PixelData->Histograms = new float*[HUHistogramsPerPixel];
              for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                PixelData->Histograms[i2] = new float[HUHistogramBins];
              PixelData->PreviousHistogram = new float[HUHistogramBins];

              for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
              {
                memcpy(PixelData->Histograms[i], CurrentHistogram, HUHistogramBins * sizeof(float));
                PixelData->Weights[i] = 1.0 / HUHistogramsPerPixel;
                PixelData->BackgroundHistogram[i] = true;
              }
              PixelData->BackgroundRate = 1.0;
              PixelData->LifeCycle = 0;
              memcpy(PixelData->PreviousHistogram, CurrentHistogram, HUHistogramBins * sizeof(float));

              model[(HUImageWidth - 1) / 2][y] = PixelData;
            }
            else {
              bool InitHistograms = (MDDataState == ps_Initialized);

              if (MDDataState != ps_Initialized && HUOFCamMovement)
              {
                // Histogram intersection between the previous and the current histogram
                float Difference = 0.0;
                for (int i1 = HUHistogramBins - 1; i1 >= 0; --i1)
                {
                  Difference += (float)(CurrentHistogram[i1] < PixelData->PreviousHistogram[i1] ?
                    CurrentHistogram[i1] : PixelData->PreviousHistogram[i1]);
                }
                Difference /= HUSamplePixels;

                if (Difference < HUBackgrThres)
                  InitHistograms = true;
              }
              if (InitHistograms)
              {
                // Copy the histogram data to the HU data structures
                for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
                {
                  memcpy(PixelData->Histograms[i], CurrentHistogram, HUHistogramBins * sizeof(float));
                  PixelData->Weights[i] = 1.0 / HUHistogramsPerPixel;
                  PixelData->BackgroundHistogram[i] = true;
                }
                memcpy(PixelData->PreviousHistogram, CurrentHistogram, HUHistogramBins * sizeof(float));
                PixelData->BackgroundRate = 1.0;
                PixelData->LifeCycle = 0;
              }
              else {
                // Update the HU data structures
                UpdateHUPixelData(PixelData, CurrentHistogram);

                if (MDMode == md_DLBPHistograms)
                {
                  memcpy(PixelData->PreviousHistogram, CurrentHistogram, HUHistogramBins * sizeof(float));
                }
              }
            }
          }

          // Copy the histogram
          memcpy(CurrentHistogram2, CurrentHistogram, HUHistogramBins * sizeof(float));

          // This cycle generates a column of histograms
          for (int x = HUImageWidth - 2; x >= 0; --x)
          {
            RowStart = RowWidth*y;

            // Delete and add a pixel column from the histogram data
            for (int i = HUHistogramArea - 1; i >= 0; --i)
            {
              if (HUMaskRowAddDel[i][0] != -1)
                CurrentHistogram2[ImgData[RowStart + x + HUMaskRowAddDel[i][0]]]++;
              if (HUMaskRowAddDel[i][1] != -1)
                CurrentHistogram2[ImgData[RowStart + x + HUMaskRowAddDel[i][1]]]--;

              RowStart += RowWidth;
            }
            if (x % 2 == 0)
            {
              MEPixelDataType* PixelData = model[x / 2][y];

              // Allocate and initialize the pixel data if needs be
              if (!PixelData)
              {
                // Memory allocation
                PixelData = new MEPixelDataType;
                PixelData->Weights = new float[HUHistogramsPerPixel];
                PixelData->BackgroundHistogram = new bool[HUHistogramsPerPixel];
                PixelData->Histograms = new float*[HUHistogramsPerPixel];
                for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                  PixelData->Histograms[i2] = new float[HUHistogramBins];
                PixelData->PreviousHistogram = new float[HUHistogramBins];

                for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
                {
                  memcpy(PixelData->Histograms[i], CurrentHistogram2, sizeof(CurrentHistogram2));
                  PixelData->Weights[i] = 1.0 / HUHistogramsPerPixel;
                  PixelData->BackgroundHistogram[i] = true;
                }
                PixelData->BackgroundRate = 1.0;
                PixelData->LifeCycle = 0;
                model[x / 2][y] = PixelData;
                memcpy(PixelData->PreviousHistogram, CurrentHistogram2, sizeof(CurrentHistogram2));
              }
              else {
                bool InitHistograms = (MDDataState == ps_Initialized);

                if (MDDataState != ps_Initialized && HUOFCamMovement)
                {
                  // Histogram intersection between the previous and the current histogram
                  float Difference = 0.0;
                  for (int i1 = HUHistogramBins - 1; i1 >= 0; --i1)
                  {
                    Difference += (float)(CurrentHistogram2[i1] < PixelData->PreviousHistogram[i1] ?
                      CurrentHistogram2[i1] : PixelData->PreviousHistogram[i1]);
                  }
                  Difference /= HUSamplePixels;

                  if (Difference < HUBackgrThres)
                    InitHistograms = true;
                }
                if (InitHistograms)
                {
                  // Copy the histogram data to the HU data structures
                  for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
                  {
                    memcpy(PixelData->Histograms[i], CurrentHistogram2, sizeof(CurrentHistogram2));
                    PixelData->Weights[i] = 1.0 / HUHistogramsPerPixel;
                    PixelData->BackgroundHistogram[i] = true;
                  }
                  memcpy(PixelData->PreviousHistogram, CurrentHistogram2, sizeof(CurrentHistogram2));
                  PixelData->BackgroundRate = 1.0;
                  PixelData->LifeCycle = 0;
                }
                else {
                  // Update the HU data structures
                  UpdateHUPixelData(PixelData, CurrentHistogram2);

                  if (MDMode == md_DLBPHistograms)
                  {
                    memcpy(PixelData->PreviousHistogram, CurrentHistogram2, sizeof(CurrentHistogram2));
                  }
                }
              }
            }

          }
        }
        delete[] CurrentHistogram;
        delete[] CurrentHistogram2;
      }

      void MotionDetection::UpdateHUPixelData(MEPixelDataType* PixelData, const float *histogram)
      {
        int MaxIndex = 0;
        float MaxValue = -1;
        bool Replace = true;
        float *IntersectionResults = new float[HUHistogramsPerPixel];

        PixelData->LifeCycle++;
        PixelData->BackgroundRate = 0.0;

        // Compute intersection between the currect and older histograms
        for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
        {
          // Histogram intersection
          float Difference = 0.0;
          for (int i1 = HUHistogramBins - 1; i1 >= 0; --i1)
          {
            Difference += (float)histogram[i1] < PixelData->Histograms[i][i1] ?
              (float)histogram[i1] : PixelData->Histograms[i][i1];
          }

          IntersectionResults[i] = (float)Difference / (float)(HUSamplePixels);

          if (PixelData->BackgroundHistogram[i] &&
            IntersectionResults[i] > PixelData->BackgroundRate)
          {
            PixelData->BackgroundRate = IntersectionResults[i];
          }

          if (MaxValue < IntersectionResults[i])
          {
            MaxValue = IntersectionResults[i];
            MaxIndex = i;
          }

          Replace = Replace && (IntersectionResults[i] < HUPrThres);
        }

        // Replace the histogram with the lowest weight
        if (Replace)
        {
          // Find the histogram with minimal weight
          int MinIndex = 0;
          float MinValue = PixelData->Weights[0];
          for (int i1 = HUHistogramsPerPixel - 1; i1 > 0; --i1)
          {
            if (MinValue > PixelData->Weights[i1])
            {
              MinValue = PixelData->Weights[i1];
              MinIndex = i1;
            }
          }

          PixelData->Weights[MinIndex] = 0.01;
          for (int i1 = HUHistogramBins - 1; i1 >= 0; --i1)
            PixelData->Histograms[MinIndex][i1] = (float)histogram[i1];
          PixelData->BackgroundHistogram[MinIndex] = 0;

          // Normalize the weights
          float sum = 0;
          for (int i1 = HUHistogramsPerPixel - 1; i1 >= 0; --i1)
            sum += PixelData->Weights[i1];

          for (int i1 = HUHistogramsPerPixel - 1; i1 >= 0; --i1)
            PixelData->Weights[i1] = PixelData->Weights[i1] / sum;

          return;
        }

        float LearningRate = HUHistLRate;

        if (PixelData->LifeCycle < 100)
          LearningRate += (float)(100 - PixelData->LifeCycle) / 100;
        else
          if (MDMode == md_DLBPHistograms && HUOFFrames != -1 && HUOFFrames < 40)
            LearningRate += (HUOFFrames < 80 ? 0.05 : 0);

        // Match was found -> Update the histogram of the best match
        for (int i = HUHistogramBins - 1; i >= 0; --i)
        {
          PixelData->Histograms[MaxIndex][i] *= (1.0 - LearningRate);
          PixelData->Histograms[MaxIndex][i] += LearningRate*(float)histogram[i];
        }

        LearningRate = HUWeightsLRate;
        if (PixelData->LifeCycle < 100)
          LearningRate += (float)(100 - PixelData->LifeCycle) / 100;
        else
          if (MDMode == md_DLBPHistograms && HUOFFrames != -1 && HUOFFrames < 40)
            LearningRate += (HUOFFrames < 80 ? 0.05 : 0);

        // Update the weights of the histograms
        for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
        {
          PixelData->Weights[i] =
            (LearningRate*(i == MaxIndex) + (1.0 - LearningRate)*PixelData->Weights[i]);
        }

        // Order and select the background histograms
        float **Weights = new float*[HUHistogramsPerPixel];
        for (int i = 0; i < HUHistogramsPerPixel; ++i)
          Weights[i] = new float[2];

        for (int i = HUHistogramsPerPixel - 1; i >= 0; --i)
        {
          Weights[i][0] = (float)i;
          Weights[i][1] = PixelData->Weights[i];
        }

        for (int i1 = HUHistogramsPerPixel - 1; i1 >= 2; --i1)
          for (int i = i1; i >= 1; --i)
          {
            if (Weights[i][1] <= Weights[i - 1][1])
            {
              float tmp = Weights[i][0];
              float tmp2 = Weights[i][1];

              Weights[i][0] = Weights[i - 1][0];
              Weights[i][1] = Weights[i - 1][1];

              Weights[i - 1][0] = tmp;
              Weights[i - 1][1] = tmp2;
            }
          }

        float Sum = 0;
        int i = 0;

        for (i = HUHistogramsPerPixel - 1; i >= 0; --i)
        {
          Sum += Weights[i][1];
          PixelData->BackgroundHistogram[(int)Weights[i][0]] = true;

          if (Sum > HUBackgrThres)
            break;
        }
        for (int i1 = i - 1; i1 >= 0; --i1)
        {
          PixelData->BackgroundHistogram[(int)Weights[i1][0]] = false;
        }
        delete[] IntersectionResults;
        for (int i = 0; i < HUHistogramsPerPixel; ++i)
          delete[] Weights[i];
        delete[] Weights;
      }

      void MotionDetection::OpticalFlowCorrection()
      {
        IplImage *PreviousGray = NULL, *CurrentGray = NULL;
        char* PointsStatus = (char*)cvAlloc(HUOFPointsNumber);
        int i = 0, i1 = 0;

        if (HUOFFrames != -1)
          HUOFFrames++;

        // Convert the images into grayscale
        if (CurrentImage.GetLayers() > 1)
        {
          CurrentGray = cvCreateImage(cvGetSize(CurrentImage.GetIplImage()), IPL_DEPTH_8U, 1);
          cvCvtColor(CurrentImage.GetIplImage(), CurrentGray, CV_BGR2GRAY);
        }
        else
          CurrentGray = (IplImage*)CurrentImage.GetIplImage();
        if (PreviousImage.GetLayers() > 1)
        {
          PreviousGray = cvCreateImage(cvGetSize(CurrentImage.GetIplImage()), IPL_DEPTH_8U, 1);
          cvCvtColor(PreviousImage.GetIplImage(), PreviousGray, CV_BGR2GRAY);
        }
        else
          PreviousGray = (IplImage*)PreviousImage.GetIplImage();

        if (HUOFDataState != ps_Successful)
        {
          printf("Search new corners\n");
          IplImage* TempEig = cvCreateImage(cvGetSize(CurrentGray), 32, 1);
          IplImage* Temp = cvCreateImage(cvGetSize(CurrentGray), 32, 1);
          double MinDistance = (CurrentImage.GetWidth() + CurrentImage.GetHeight()) / 20;
          HUOFPointsNumber = MaxTrackedPoints = CurrentImage.GetWidth()*CurrentImage.GetHeight() / 1000;

          // Search good trackable points
          cvGoodFeaturesToTrack(PreviousGray, TempEig, Temp,
            (CvPoint2D32f*)HUOFPoints[0], &HUOFPointsNumber,
            0.01, MinDistance, NULL, 3);
          MaxTrackedPoints = HUOFPointsNumber;
          // Release temporary images
          cvReleaseImage(&TempEig);
          cvReleaseImage(&Temp);
          // Realloc the point status array
          if (PointsStatus)
          {
            cvFree(&PointsStatus);
            PointsStatus = NULL;
          }

          if (MaxTrackedPoints < 2)
          {
            HUOFDataState = ps_Initialized;
            HUOFPointsNumber = CurrentImage.GetWidth()*CurrentImage.GetHeight() / 1000;
            return;
          }
          else
            HUOFDataState = ps_Successful;
          PointsStatus = (char*)cvAlloc(HUOFPointsNumber);
        }

        cvCalcOpticalFlowPyrLK(PreviousGray, CurrentGray, HUOFPrevPyramid, HUOFPyramid,
          HUOFPoints[0], HUOFPoints[1], HUOFPointsNumber,
          cvSize(10, 10), 3, PointsStatus, NULL,
          cvTermCriteria(CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 5, 1), 0);

        // Count the distances of the tracked points
        int **Distances = new int*[HUOFPointsNumber];
        for (int i = 0; i < HUOFPointsNumber; ++i)
          Distances[i] = new int[3];

        int DistanceMax = 0;
        for (i = 0; i < HUOFPointsNumber; ++i)
        {
          int DiffX = (int)MERound(HUOFPoints[1][i].x - HUOFPoints[0][i].x);
          int DiffY = (int)MERound(HUOFPoints[1][i].y - HUOFPoints[0][i].y);
          if ((PointsStatus[i] == 1) && !((DiffX == 0) && (DiffY == 0)))
          {
            bool found = false;
            // Create a list from the differences to count them
            for (i1 = 0; i1 < DistanceMax; ++i1)
            {
              if ((Distances[i1][0] == DiffX) &&
                (Distances[i1][1] == DiffY))
              {
                Distances[i1][2]++;
                found = true;
                break;
              }
            }
            if ((!found) && !((DiffX == 0) && (DiffY == 0)))
            {
              Distances[DistanceMax][0] = (int)MERound(HUOFPoints[1][i].x - HUOFPoints[0][i].x);
              Distances[DistanceMax][1] = (int)MERound(HUOFPoints[1][i].y - HUOFPoints[0][i].y);
              Distances[DistanceMax][2] = 1;
              DistanceMax++;
            }
          }
        }

        // Sort the results
        for (int i1 = DistanceMax - 1; i1 >= 2; --i1)
        {
          for (int i = i1; i >= 1; --i)
          {
            if ((Distances[i][2] > Distances[i - 1][2]) ||
              ((Distances[i][2] == Distances[i - 1][2]) &&
              (abs(Distances[i][0]) + abs(Distances[i][1]) <
                abs(Distances[i - 1][0]) + abs(Distances[i - 1][1]))))
            {
              int tmp = Distances[i][0];
              int tmp2 = Distances[i][1];
              int tmp3 = Distances[i][2];

              Distances[i][0] = Distances[i - 1][0];
              Distances[i][1] = Distances[i - 1][1];
              Distances[i][2] = Distances[i - 1][2];

              Distances[i - 1][0] = tmp;
              Distances[i - 1][1] = tmp2;
              Distances[i - 1][2] = tmp3;
            }
          }
        }

        float MoveX = 0.0;
        float MoveY = 0.0;
        int SampleNums = 0;
        float DistanceMeasure = 0.0;

        // Calculate the final camera movement
        for (i = 0; i < DistanceMax; ++i)
        {
          if ((Distances[i][2] <= MaxTrackedPoints / 10))
            break;

          if (i > 0)
          {
            DistanceMeasure += (Distances[i][0] - Distances[i - 1][0])*(Distances[i][0] - Distances[i - 1][0]);
            DistanceMeasure += (Distances[i][1] - Distances[i - 1][1])*(Distances[i][1] - Distances[i - 1][1]);
          }

          MoveX += Distances[i][0] * Distances[i][2];
          MoveY += Distances[i][1] * Distances[i][2];
          SampleNums += Distances[i][2];
        }

        if (SampleNums > 0)
        {
          MoveX = MERound(MoveX / SampleNums);
          MoveY = MERound(MoveY / SampleNums);
        }

        if (!((MoveX == 0) && (MoveY == 0)) &&
          (SampleNums > MaxTrackedPoints / 2))
        {
          HUOFCamMovementX += (int)MoveX;
          int HUOFCamMovementY = (int)MoveY;
          int MaxX = (HUImageWidth / 2) - 1;
          int MaxY = HUImageHeight - 1;
          /*
          printf("-----------\n");

          for (i = 0; i < DistanceMax; ++i)
          printf("%d: %d,%d\n", Distances[i][2], Distances[i][0], Distances[i][1]);

          printf("FINAL: %d,%d,%1.2f\n", (int)MoveX, (int)MoveY, DistanceMeasure);
          printf("-----------\n");
          printf("Camera movement: %d,%d,%d (max: %d, current: %d)\n",
          SampleNums, HUOFCamMovementX, HUOFCamMovementY, MaxTrackedPoints, HUOFPointsNumber);
          */
          HUOFFrames = 0;
          HUOFCamMovement = true;

          if (!(HUOFCamMovementY == 0 && HUOFCamMovementX >= -1 && HUOFCamMovementX <= 1))
          {
            MEPixelDataType ***PreviousData = new MEPixelDataType**[MaxX + 1];

            for (int i = 0; i < MaxX + 1; ++i)
              PreviousData[i] = new MEPixelDataType*[MaxY + 1];

            // Camera movement being happened
            for (int y = MaxY; y >= 0; --y)
            {
              for (int x = MaxX; x >= 0; --x)
              {
                PreviousData[x][y] = NULL;
              }
            }

            // Move the LBP data to new locations
            for (int y = MaxY; y >= 0; --y)
            {
              for (int x = MaxX; x >= 0; --x)
              {
                int NewX = x + (HUOFCamMovementX / 2);
                int NewY = y + HUOFCamMovementY;

                if (NewX >= 0 && NewX <= MaxX &&
                  NewY >= 0 && NewY <= MaxY)
                {
                  if (HULBPPixelData[NewX][NewY])
                  {
                    PreviousData[NewX][NewY] = HULBPPixelData[NewX][NewY];
                    HULBPPixelData[NewX][NewY] = NULL;
                    if (PreviousData[x][y])
                    {
                      HULBPPixelData[NewX][NewY] = PreviousData[x][y];
                      PreviousData[x][y] = NULL;
                    }
                    else
                    {
                      HULBPPixelData[NewX][NewY] = HULBPPixelData[x][y];
                      HULBPPixelData[x][y] = NULL;
                    }
                  }
                  else
                  {
                    if (PreviousData[x][y])
                    {
                      HULBPPixelData[NewX][NewY] = PreviousData[x][y];
                      PreviousData[x][y] = NULL;
                    }
                    else
                    {
                      HULBPPixelData[NewX][NewY] = HULBPPixelData[x][y];
                      HULBPPixelData[x][y] = NULL;
                    }
                  }
                }
                else
                {
                  if (HULBPPixelData[x][y])
                  {
                    delete[] HULBPPixelData[x][y]->PreviousHistogram;
                    for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                      delete[] HULBPPixelData[x][y]->Histograms[i2];
                    delete[] HULBPPixelData[x][y]->Histograms;
                    delete[] HULBPPixelData[x][y]->BackgroundHistogram;
                    delete[] HULBPPixelData[x][y]->Weights;
                    delete HULBPPixelData[x][y];
                    HULBPPixelData[x][y] = NULL;
                  }
                }
              }
            }

            // Release unused data
            for (int y = MaxY; y >= 0; --y)
            {
              for (int x = MaxX; x >= 0; --x)
              {
                if (PreviousData[x][y])
                {
                  delete[] PreviousData[x][y]->PreviousHistogram;
                  for (int i2 = 0; i2 < HUHistogramsPerPixel; ++i2)
                    delete[] PreviousData[x][y]->Histograms[i2];
                  delete[] PreviousData[x][y]->Histograms;
                  delete[] PreviousData[x][y]->BackgroundHistogram;
                  delete[] PreviousData[x][y]->Weights;
                  delete PreviousData[x][y];
                  PreviousData[x][y] = NULL;
                }
              }
            }

            HUOFCamMovementX = HUOFCamMovementX % 1;

            for (int i = 0; i < MaxX + 1; ++i)
              delete[] PreviousData[i];
            delete[] PreviousData;
          }
        }

        i1 = 0;
        // Throw the missed points away
        for (i = 0; i < HUOFPointsNumber; ++i)
        {
          if (PointsStatus[i] == 1)
          {
            HUOFPoints[0][i1] = HUOFPoints[1][i];
            i1++;
          }
        }
        HUOFPointsNumber -= i + 1 - i1;

        if (HUOFPointsNumber < MaxTrackedPoints / 2)
        {
          printf("Re-init the optical flow\n");
          HUOFDataState = ps_Initialized;
          HUOFPointsNumber = CurrentImage.GetWidth()*CurrentImage.GetHeight() / 1000;
        }
        // Free memory
        if (PreviousGray != PreviousImage.GetIplImage())
          cvReleaseImage(&PreviousGray);
        if (CurrentGray != CurrentImage.GetIplImage())
          cvReleaseImage(&CurrentGray);
        cvFree(&PointsStatus);

        for (int i = 0; i < HUOFPointsNumber; ++i)
          delete[] Distances[i];
        delete[] Distances;
      }

      void MotionDetection::GetMotionsMaskHU(MEImage& mask_image)
      {
        if (MDDataState != ps_Successful)
        {
          mask_image.Clear();
          return;
        }

        // Reallocate the mask image if needs be
        if ((HUImageWidth + HUHistogramArea - 1 != mask_image.GetWidth()) ||
          (HUImageHeight + HUHistogramArea - 1 != mask_image.GetHeight()) ||
          (mask_image.GetLayers() != 1))
        {
          mask_image.Realloc(HUImageWidth + HUHistogramArea - 1,
            HUImageHeight + HUHistogramArea - 1, 1);
        }
        mask_image.Clear();
        // Generate the mask image
        unsigned char* MaskImgData = mask_image.GetImageData();
        int RowStart = (mask_image.GetHeight() - HUHistogramArea / 2)*mask_image.GetRowWidth();
        int RowWidth = mask_image.GetRowWidth();

        // Generate a graph about the histogram data
        Graph::node_id **Nodes = new Graph::node_id*[HUImageWidth / 2];
        for (int i = 0; i < HUImageWidth / 2; ++i)
          Nodes[i] = new Graph::node_id[HUImageHeight];
        Graph *LBPGraph = new Graph();

        for (int x = (HUImageWidth / 2) - 1; x >= 0; --x)
        {
          for (int y = HUImageHeight - 1; y >= 0; --y)
          {
            Nodes[x][y] = LBPGraph->add_node();
          }
        }

        for (int x = (HUImageWidth / 2) - 1; x >= 0; --x)
        {
          for (int y = HUImageHeight - 1; y >= 0; --y)
          {
            LBPGraph->set_tweights(Nodes[x][y], 1,
              (short int)(HUMinCutWeight*(1 - HULBPPixelData[x][y]->BackgroundRate)));

            if (x > 0 && y > 0)
            {
              LBPGraph->add_edge(Nodes[x][y], Nodes[x - 1][y], 1, 1);
              LBPGraph->add_edge(Nodes[x][y], Nodes[x][y - 1], 1, 1);
            }
          }
        }

        LBPGraph->maxflow();

        for (int x = (HUImageWidth / 2) - 1; x >= 0; --x)
        {
          for (int y = HUImageHeight - 1; y >= 0; --y)
          {
            if (LBPGraph->what_segment(Nodes[x][y]) == Graph::SINK)
              HULBPPixelData[x][y]->BackgroundRate = 0.0;
            else
              HULBPPixelData[x][y]->BackgroundRate = 1.0;
          }
        }

        delete LBPGraph;
        LBPGraph = NULL;
        for (int y = HUImageHeight - 1; y >= 0; --y)
        {
          for (int x = HUImageWidth - 1; x >= 0; --x)
          {
            if (y % 2 == (x + 1) % 2)
              MaskImgData[RowStart + x + (HUHistogramArea / 2)] =
              (HULBPPixelData[x / 2][y]->BackgroundRate == 0.0) ? 255 : 0;
            else
            {
              MaskImgData[RowStart + x + (HUHistogramArea / 2)] =
                ((int)(x > 1 && HULBPPixelData[(x / 2) - 1][y]->BackgroundRate == 0.0) +
                (int)(x < mask_image.GetWidth() - HUHistogramArea - 1 &&
                  HULBPPixelData[(x / 2) + 1][y]->BackgroundRate == 0.0) +
                  (int)(y > 0 && HULBPPixelData[x / 2][y - 1]->BackgroundRate == 0.0) +
                  (int)(y < mask_image.GetHeight() - HUHistogramArea &&
                    HULBPPixelData[x / 2][y + 1]->BackgroundRate == 0.0) > 1)
                ? 255 : 0;
            }
          }
          RowStart -= RowWidth;
        }

        cvFloodFill(mask_image.GetIplImage(), cvPoint(0, 0), cvScalar(128, 128, 128, 128),
          cvScalar(0, 0, 0, 0), cvScalar(0, 0, 0, 0));
        for (int i = ((IplImage*)mask_image.GetIplImage())->widthStep*((IplImage*)mask_image.GetIplImage())->height - 1; i >= 0; --i)
        {
          if (MaskImgData[i] == 128)
          {
            MaskImgData[i] = 0;
          }
          else
          {
            if (MaskImgData[i] == 0)
            {
              MaskImgData[i] = 255;
            }
          }
        }
        // Apply an erode operator
        mask_image.Erode(1);

        for (int i = 0; i < HUImageWidth / 2; ++i)
          delete[] Nodes[i];
        delete[] Nodes;
      }

      void MotionDetection::SetSampleMaskHU(SampleMaskType mask_type, int desiredarea)
      {
        if (HUMaskColumnAddDel == NULL || HUMaskRowAddDel == NULL)
        {
          printf("Auxiliary variables are NULL\n");
          return;
        }

        // Generate a mask for computing the histograms
        IplImage *MaskImage = cvCreateImage(cvSize(HUHistogramArea, HUHistogramArea), 8, 1);
        int DesiredArea = desiredarea <= 0 ? HUHistogramBins * 2 : desiredarea;

        int **CalculationMask = new int*[HUHistogramArea];
        for (int i = 0; i < HUHistogramArea; ++i)
          CalculationMask[i] = new int[HUHistogramArea];

        int SquareSide = (int)MERound(sqrt((float)DesiredArea));
        int CircleRadius = (int)MERound(sqrt((float)DesiredArea / ME_PI_VALUE));
        int EllipseA = (int)MERound(HUHistogramArea / 2 + 1);
        int EllipseB = (int)MERound(DesiredArea / (EllipseA*1.2*ME_PI_VALUE));

        cvSetZero(MaskImage);

        switch (mask_type)
        {
        case sm_Circle:
          cvCircle(MaskImage, cvPoint(HUHistogramArea / 2, HUHistogramArea / 2),
            CircleRadius, CV_RGB(1, 1, 1), -1);
          break;

        case sm_Square:
          cvRectangle(MaskImage,
            cvPoint(HUHistogramArea / 2 - SquareSide / 2, HUHistogramArea / 2 - SquareSide / 2),
            cvPoint(HUHistogramArea / 2 + SquareSide / 2, HUHistogramArea / 2 + SquareSide / 2),
            CV_RGB(1, 1, 1), -1);
          break;

        case sm_Ellipse:
          cvEllipse(MaskImage, cvPoint(HUHistogramArea / 2, HUHistogramArea / 2),
            cvSize(EllipseA, EllipseB), 45, 0, 360,
            CV_RGB(1, 1, 1), -1);
          break;

        case sm_RandomPixels:
          HUSamplePixels = 0;
          while (HUSamplePixels != DesiredArea)
          {
            int i = rand() % HUHistogramArea;
            int j = rand() % HUHistogramArea;

            if (MaskImage->imageData[i*MaskImage->widthStep + j] == 0)
            {
              MaskImage->imageData[i*MaskImage->widthStep + j] = 1;
              HUSamplePixels++;
            }
          }
          break;

        default:
          cvCircle(MaskImage, cvPoint(HUHistogramArea / 2, HUHistogramArea / 2),
            (int)MERound(sqrt((float)DesiredArea / ME_PI_VALUE)), CV_RGB(1, 1, 1), -1);
          break;
        }

        HUSamplePixels = 0;
        //memset(CalculationMask, 0, sizeof(CalculationMask));

        for (int i = 0; i < HUHistogramArea; ++i)
        {
          for (int i1 = 0; i1 < HUHistogramArea; ++i1)
          {
            if (MaskImage->imageData[i*MaskImage->widthStep + i1] != 0)
            {
              HUSamplePixels++;
              CalculationMask[i][i1] = 1;
            }
            else {
              CalculationMask[i][i1] = 0;
            }
          }
        }

        // Fill an auxiliary variable for fast computing with data
        for (int i = 0; i < HUHistogramArea; ++i)
        {
          HUMaskColumnAddDel[i][0] = -1;
          for (int i1 = 0; i1 < HUHistogramArea; ++i1)
          {
            if (CalculationMask[i][i1] != 0)
            {
              HUMaskColumnAddDel[i][0] = i1;
              break;
            }
          }
          HUMaskColumnAddDel[i][1] = -1;
          for (int i1 = HUHistogramArea - 1; i1 >= 0; --i1)
          {
            if (CalculationMask[i][i1] != 0)
            {
              HUMaskColumnAddDel[i][1] = i1 + 1;
              break;
            }
          }
        }

        // Fill an auxiliary variable for fast computing with data
        for (int i = 0; i < HUHistogramArea; ++i)
        {
          HUMaskRowAddDel[i][0] = -1;
          for (int i1 = 0; i1 < HUHistogramArea; ++i1)
          {
            if (CalculationMask[i1][i] != 0)
            {
              HUMaskRowAddDel[i][0] = i1;
              break;
            }
          }
          HUMaskRowAddDel[i][1] = -1;
          for (int i1 = HUHistogramArea - 1; i1 >= 0; --i1)
          {
            if (CalculationMask[i1][i] != 0)
            {
              HUMaskRowAddDel[i][1] = i1 + 1;
              break;
            }
          }
        }

        // Freeing memory
        cvReleaseImage(&MaskImage);

        for (int i = 0; i < HUHistogramArea; ++i)
          delete[] CalculationMask[i];
        delete[] CalculationMask;
      }
    }
  }
}

#endif
